Inter-laboratory study of human in vitro toxicogenomics-based tests as alternative methods for evaluating chemical carcinogenicity: a bioinformatics perspective

GADD45 in Stress Signaling, Cell Cycle Control, and Apoptosis

GADD45 is a gene family consisting of GADD45A, GADD45B, and GADD45G that is often induced by DNA damage and other stress signals associated with growth arrest and apoptosis. Many of these roles are carried out via signaling mediated by p38 mitogen-activated protein kinases (MAPKs). The GADD45 proteins can contribute to p38 activation either by activation of upstream kinase(s) or by direct interaction, as well as suppression of p38 activity in certain cases. In vivo, there are important tissue and cell type specific differences in the roles for GADD45 in MAPK signaling. In addition to being p53-regulated, GADD45A has also been found to contribute to p53 activation via p38. Like other stress and signaling proteins, GADD45 proteins show complex regulation and numerous effectors. More recently, aberrant GADD45 expression has been found in several human cancers, but the mechanisms behind these findings largely remain to be understood.

ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets

In the past few decades, major initiatives have been launched around the world to address chemical safety testing. These efforts aim to innovate and improve the efficacy of existing methods with the long-term goal of developing new risk assessment paradigms. The transcriptomic and toxicological profiling of mammalian cells has resulted in the creation of multiple toxicogenomic datasets and corresponding tools for analysis. To enable easy access and analysis of these valuable toxicogenomic data, we have developed ToxicoDB (toxicodb.ca), a free and open cloud-based platform integrating data from large in vitro toxicogenomic studies, including gene expression profiles of primary human and rat hepatocytes treated with 231 potential toxicants. To efficiently mine these complex toxicogenomic data, ToxicoDB provides users with harmonized chemical annotations, time- and dose-dependent plots of compounds across datasets, as well as the toxicity-related pathway analysis. The data in ToxicoDB have been generated using our open-source R package, ToxicoGx (github.com/bhklab/ToxicoGx). Altogether, ToxicoDB provides a streamlined process for mining highly organized, curated, and accessible toxicogenomic data that can be ultimately applied to preclinical toxicity studies and further our understanding of adverse outcomes.

Toward Rigorous Materials Production: New Approach Methodologies Have Extensive Potential to Improve Current Safety Assessment Practices

Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high-throughput and high-content screening assays, dose-response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer-by-design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation.

A novel, integrated in vitro carcinogenicity test to identify genotoxic and non-genotoxic carcinogens using human lymphoblastoid cells

Human exposure to carcinogens occurs via a plethora of environmental sources, with 70-90% of cancers caused by extrinsic factors. Aberrant phenotypes induced by such carcinogenic agents may provide universal biomarkers for cancer causation. Both current in vitro genotoxicity tests and the animal-testing paradigm in human cancer risk assessment fail to accurately represent and predict whether a chemical causes human carcinogenesis. The study aimed to establish whether the integrated analysis of multiple cellular endpoints related to the Hallmarks of Cancer could advance in vitro carcinogenicity assessment. Human lymphoblastoid cells (TK6, MCL-5) were treated for either 4 or 23 h with 8 known in vivo carcinogens, with doses up to 50% Relative Population Doubling (maximum 66.6 mM). The adverse effects of carcinogens on wide-ranging aspects of cellular health were quantified using several approaches; these included chromosome damage, cell signalling, cell morphology, cell-cycle dynamics and bioenergetic perturbations. Cell morphology and gene expression alterations proved particularly sensitive for environmental carcinogen identification. Composite scores for the carcinogens' adverse effects revealed that this approach could identify both DNA-reactive and non-DNA reactive carcinogens in vitro. The richer datasets generated proved that the holistic evaluation of integrated phenotypic alterations is valuable for effective in vitro risk assessment, while also supporting animal test replacement. Crucially, the study offers valuable insights into the mechanisms of human carcinogenesis resulting from exposure to chemicals that humans are likely to encounter in their environment. Such an understanding of cancer induction via environmental agents is essential for cancer prevention.

Computational Network Analysis for Drug Toxicity Prediction

The computational prediction of compound effects from molecular data is an important task in hazard and risk assessment and pivotal for judging the safety of any drug, chemical or cosmetic compound. In particular, the identification of such compound effects at the level of molecular interaction networks can be helpful for the construction of adverse outcome pathways (AOPs). AOPs emerged as a guiding concept for toxicity prediction, because of the inherent mechanistic information of such networks. In fact, integrating molecular interactions in transcriptome analysis and observing expression changes in closely interacting genes might allow identifying the key molecular initiating events of compound toxicity.In this work we describe a computational approach that is suitable for the identification of such network modules from transcriptomics data, which is the major molecular readout of toxicogenomics studies. The approach is composed of different tools (1) for primary data analysis, i.e., the biostatistical quantification of the gene expression changes, (2) for functional annotation and prioritization of genes using literature mining, as well as (3) for the construction of an interaction network that consists of interactions with high confidence and the identification of predictive modules from these networks. We describe the different steps of the approach and demonstrate its performance with public data on drugs that induce hepatic and cardiac toxicity.

3S - Systematic, systemic, and systems biology and toxicology

A biological system is more than the sum of its parts - it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass "systemic toxicities"; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to reca-pitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organ-on-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the chal-lenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.

Moving forward in carcinogenicity assessment: Report of an EURL ECVAM/ESTIV workshop

There is an increased need to develop novel alternative approaches to the two-year rodent bioassay for the carcinogenicity assessment of substances where the rodent bioassay is still a basic requirement, as well as for those substances where animal use is banned or limited or where information gaps are identified within legislation. The current progress in this area was addressed in a EURL ECVAM- ESTIV workshop held in October 2016, in Juan les Pins. A number of initiatives were presented and discussed, including data-driven, technology-driven and pathway-driven approaches. Despite a seemingly diverse range of strategic developments, commonalities are emerging. For example, providing insight into carcinogenicity mechanisms is becoming an increasingly appreciated aspect of hazard assessment and is suggested to be the best strategy to drive new developments. Thus, now more than ever, there is a need to combine and focus efforts towards the integration of available information between sectors. Such cross-sectorial harmonisation will aid in building confidence in new approach methods leading to increased implementation and thus a decreased necessity for the two-year rodent bioassay.

Validation of Transcriptomics-Based In Vitro Methods

The field of transcriptomics has expanded rapidly during the last decades. This methodology provides an exceptional framework to study not only molecular changes underlying the adverse effects of a given compound, but also to understand its Mode of Action (MoA). However, the implementation of transcriptomics-based tests within the regulatory arena is not a straightforward process. One of the major obstacles in their regulatory implementation is still the interpretation of this new class of data and the judgment of the level of confidence of these tests. A key element in the regulatory acceptance of transcriptomics-based tests is validation, which still represents a major challenge. Although important advances have been made in the development and standardisation of such tests, to date there is limited experience with their validation. Taking into account the experience acquired so far, this chapter describes those aspects that were identified as important in the validation process of transcriptomics-based tests, including the assessment of standardisation, reliability and relevance. It also critically discusses the challenges posed to validation in relation to the specific characteristics of these approaches and their application in the wider context of testing strategies.

Stem Cell Transcriptome Responses and Corresponding Biomarkers That Indicate the Transition from Adaptive Responses to Cytotoxicity

Analysis of transcriptome changes has become an established method to characterize the reaction of cells to toxicants. Such experiments are mostly performed at compound concentrations close to the cytotoxicity threshold. At present, little information is available on concentration-dependent features of transcriptome changes, in particular, at the transition from noncytotoxic concentrations to conditions that are associated with cell death. Thus, it is unclear in how far cell death confounds the results of transcriptome studies. To explore this gap of knowledge, we treated pluripotent stem cells differentiating to human neuroepithelial cells (UKN1 assay) for short periods (48 h) with increasing concentrations of valproic acid (VPA) and methyl mercury (MeHg), two compounds with vastly different modes of action. We developed various visualization tools to describe cellular responses, and the overall response was classified as "tolerance" (minor transcriptome changes), "functional adaptation" (moderate/strong transcriptome responses, but no cytotoxicity), and "degeneration". The latter two conditions were compared, using various statistical approaches. We identified (i) genes regulated at cytotoxic, but not at noncytotoxic, concentrations and (ii) KEGG pathways, gene ontology term groups, and superordinate biological processes that were only regulated at cytotoxic concentrations. The consensus markers and processes found after 48 h treatment were then overlaid with those found after prolonged (6 days) treatment. The study highlights the importance of careful concentration selection and of controlling viability for transcriptome studies. Moreover, it allowed identification of 39 candidate "biomarkers of cytotoxicity". These could serve to provide alerts that data sets of interest may have been affected by cell death in the model system studied.